Suppose you have some rules that operate on a data payload that can have many possible combinations of data values. During testing how can you be sure that you have covered all the possibilities? Including all the possible ways the data can be bad? Running your test against production data probably won’t help. Even though you may have millions of records, chances are you won’t find every possible combination of the data. So is there a way that Corticon could help to generate test data? Yes, Of Course!
This article discusses one way to accomplish it using a vocabulary that is handcrafted for the particular data model you need to create https://community.progress.com/community_groups/corticon/m/documents/1368
But is there a way to do this more generically?
Again, Yes, of course!
The attached pdf shows how to set up a generic vocabulary (comprising entities for each of the basic data types using name value pairs) that can be used to generate test data that can be copied into your specific rule model.